SMART TRIALS: MOVING FROM SITE-CENTRIC TO PATIENT-CENTRIC CLINICAL TRIALS

Lisa A. Shipley, PhD

Rozman DVDMDG Meeting

June 14, 2018

Outline

•State of the Pharmaceutical Industry

•The Problem Statement

•Clinical Trials vs. Smart Trials

•Results of Smart Trials

•Opportunities

•Questions/Discussion

2

R&D Productivity is Declining: Eroom’s Law

3

Moore’s Law vs Eroom’s Law

4

Year of Introduction

# o

f tr

an

sis

tors

/ch

ip

The Pharmaceutical Industry Challenge: Solving Multiple Issues Simultaneously

5

Non-toxic

Non-mutagenic

Non-teratogenic

Soluble

Permeable

Metabolically Stable

Long Lasting

Modified from: Drug Discovery and Development; July 2004

PK is No Longer a Major Reason for Failure (post-2000)

6

• Understanding potential new modes of failure

• Smart Trials: better clinical data

New

challenges

History of Clinical Trials

7

J. Lind’s Scurvy

Experiment

Informed

Consent

1st Double Blind

Control Trial

Multicenter

Trials

1st Randomized

Controlled Trial

1747

Use of

Placebos

1800’s

1900’s

1940’s

2018

Gold Standard:

Randomized,

double blind,

Placebo/Active

Controlled Trial

The Current Clinical Trial Paradigm Needs Transformation

8

Confounding Influence of Adherence Site-centricity

•http://www.slideshare.net/HeatherHare/d

igital-biomarkers-for-huntington-disease-

69209772

Operational Inefficiencies

• Transcriptional errors

• Data reconciliation

• Cost of visits

Blaschke, Osterberg, Vrijens, Urquhart, 2012, Ann Rev Pharmacol Toxicol, 52:275-301

Innovations to Disrupt the Drug Development Paradigm are Here

9

patient

Disclaimer: This does not represent an

endorsement of any products or platforms by

Merck

Biometrics

Smart Trials: A Patient Centric Approach to Enriching Clinical Trial Data

Sensor enabled,

Dose Date/Time Wellness

feedback

Sensor enabled

Sampling

Date/Time Mail-in samples Real-time patient

information

Smart Tablet or Packaging Improved dosing adherence

Smart Dosing: mobile/digital technologies

to accurately monitor dose time and date

Smart Sampling Digital Biomarkers or Home Based Collected of PK or

Biomarkers

liquid

sensor

Smart Sampling: Digital or lab-based

technologies for use in the outpatient/home

setting to monitor PK, biomarkers or other

endpoints

Smart Analytics: technology to collect,

integrate and visualize data in real time

Clinical Pilot Studies: Two pilot studies conducted, similar design but using different technologies of interest

11

• Study designs:

• 2 period, fixed sequence studies

• QD sitagliptin to 16 healthy subjects

• Period 1 – “Smart” dosing & sampling (Days 1-14)

• Dosing date/time captured via smart packaging (passively) and eDiary (patient-reported)

• eDiary for date/time capture of PK samples

• In-clinic and at-home PK sampling

• DNA profiling of select PK samples for confirmation of patient ID

• Period 2 – “Traditional” dosing & sampling (Days 15-16)

• Traditional packaging

• In-clinic PK sampling

• Questionnaire for subject feedback

Smart Dosing: What is it? Electronic Monitoring of Adherence

12

Current Approaches-Smart packaging

• Automatically records dispensing event

• Passive monitoring or active remediation

• 1 MM+ data points over 20+ years

• 8 of 19 major pharma using smart dosing technology

• Battling perceptions: • “Pill counts are good enough”

• Too complex to add to aggressive clinical timelines

Subject Questionnaire Results

Smart Dosing: What Have We Learned?

13

• Most subjects found the technologies easy to use and were strong supporters

• Growing experience with a wide variety of smart dosing options

• ↑ insights into patient dosing patterns

• Noncompliant subject highlights importance of collecting this type of data

• Overall, data support future use of smart dosing in clinical trials

Smart Sampling: What is it?

14

• Aim is to develop outpatient (at-home) collection of samples that can be used for measurement of drug and/or

biomarkers

• Reduced patient burden compared to wet sampling (µL vs. mL quantities)

• Can be shipped using regular mail, does not require dry ice

• Current approaches • Fingerstick sampling, blood spotted on Dried Blood

Spot card

• Sample barcode pre-assigned to each

subject/nominal time; scanned by subject with

smart phone/e-diary upon collection and eDiary

entry

• Time/date recorded by subjects with eDiary

• DBS cards returned to clinical site and shipped to

BA lab for concentration analysis

• Future approaches • Less painful methods of sampling

• Collection on paper or polymer matrix

• Automated date/time stamps

• Sample barcode assigned at time of collection

DBS eDiary VAMS

TAP™ HemoLink

Smart Sampling Results from Pilot #1

15

Representative Individual PK Profiles: In-Clinic vs. At-Home Fingerstick DBS

Red: at-home samples collected using smart dosing & sampling methods (Mean of Days 5, 8, 11)

Blue: in-clinic samples collected using traditional methods (Mean of Days 16, 17, 18)

• Mean PK profiles were generally similar for at-home samples collected using smart dosing and

sampling methods vs. in-clinic samples collected using traditional methods

• PK and associated variability from in-clinic vs. at-home samples were similar

• Several cases of missing or incorrect barcode scans using eDiary

Smart Sampling Results from Pilot #2

16

Individual and Geometric Mean (95% CI)

Fingerstick DBS Sitagliptin Ctrough Values

At-Home In-Clinic

• eDiary data: Two subjects had missing eDiary

entries for collected PK samples

• Comparison of PK & Dosing Data: Undetectable

sitagliptin concentrations for at-home samples collected

from 2 subjects, despite reported dosing via Smart

Packaging & eDiary

– In one case, DNA profiling confirmed subject ID

potentially dispensed dose without ingestion

– In another case, DNA profiling did not confirm subject

ID suggests samples collected by someone else

• Sitagliptin concentrations from samples collected at-home were generally similar to those collected

in-clinic

• Missing eDiary data highlight importance of adding automated date/time stamps

• Smart Packaging is an improved yet imperfect indicator of adherence

• DNA profiling can be a useful tool as a means of confirming patient ID and sample disambiguation

17 17

Fingerstick DBS sampling: PK and eDiary Data

BLQ = below the limit of

quantification (5 ng/mL)

eDiary Web Portal

Ctrough C8hr Ctrough C8hr Ctrough C4hr Ctrough C1hr C8hr Ctrough C8hr

AN

Day 1,

0hr

Day 1,

1hr

Day 5,

0hr

Day 5,

8hr

Day 8,

0hr

Day 8,

8hr

Day 10,

0hr

Day 10,

4hr

Day 12,

0hr

Day 12,

1hr

Day 12,

8hr

Day 14,

0hr

Day 14,

8hr

1 BLQ 335 19 BLQ BLQ BLQ BLQ BLQ BLQ BLQ BLQ 31 119

2 BLQ 226 65 138 34 100 41 315 30 359 133 34 173

3 BLQ 161 37 172 36 151 60 420 47 326 103 36 231

4 BLQ 235 34 151 31 151 42 268 33 850 132 14 92

5 BLQ 449 25 133 24 157 27 366 32 835 141 106 196

6 BLQ 281 36 163 45 172 23 275 34 284 176 31 134

7 BLQ 143 42 215 42 172 38 312 49 511 151 44 183

8 BLQ 357 29 148 25 144 19 257 34 31 170 26 129

9 BLQ 373 27 124 29 188 26 308 33 257 108 43 151

10 BLQ 438 33 74 26 82 39 79 44 101 84 19 86

11 BLQ 416 28 132 26 115 27 157 31 516 125 BLQ 144

12 BLQ 315 BLQ 66 BLQ 65 BLQ 140 22 100 165 20 91

13 BLQ 327 40 176 38 181 42 279 45 579 132 35 161

14 BLQ 451 47 28 33 137 59 348 52 448 153 41 170

15 BLQ 411 28 155 30 missing 24 133 26 423 286 29 172

16 BLQ 164 79 273 80 229 58 53 89 78 308 78 224

Sitagliptin Concentration (ng/mL)

AN 12 PK data indicate potential missed doses on 3 at-

home study days; however, these doses were reported via

eDiary and Smart Packaging

DNA profiling confirmed patient ID

Potentially dispensed pill without ingestion

Key Take-Aways

Data suggest need for dosing confirmation in some cases (e.g. ingestible

sensors or visual dosing confirmation)

18 18

Fingerstick DBS sampling: PK and eDiary Data

BLQ = below the limit of

quantification (5 ng/mL)

eDiary Web Portal

Ctrough C8hr Ctrough C8hr Ctrough C4hr Ctrough C1hr C8hr Ctrough C8hr

AN

Day 1,

0hr

Day 1,

1hr

Day 5,

0hr

Day 5,

8hr

Day 8,

0hr

Day 8,

8hr

Day 10,

0hr

Day 10,

4hr

Day 12,

0hr

Day 12,

1hr

Day 12,

8hr

Day 14,

0hr

Day 14,

8hr

1 BLQ 335 19 BLQ BLQ BLQ BLQ BLQ BLQ BLQ BLQ 31 119

2 BLQ 226 65 138 34 100 41 315 30 359 133 34 173

3 BLQ 161 37 172 36 151 60 420 47 326 103 36 231

4 BLQ 235 34 151 31 151 42 268 33 850 132 14 92

5 BLQ 449 25 133 24 157 27 366 32 835 141 106 196

6 BLQ 281 36 163 45 172 23 275 34 284 176 31 134

7 BLQ 143 42 215 42 172 38 312 49 511 151 44 183

8 BLQ 357 29 148 25 144 19 257 34 31 170 26 129

9 BLQ 373 27 124 29 188 26 308 33 257 108 43 151

10 BLQ 438 33 74 26 82 39 79 44 101 84 19 86

11 BLQ 416 28 132 26 115 27 157 31 516 125 BLQ 144

12 BLQ 315 BLQ 66 BLQ 65 BLQ 140 22 100 165 20 91

13 BLQ 327 40 176 38 181 42 279 45 579 132 35 161

14 BLQ 451 47 28 33 137 59 348 52 448 153 41 170

15 BLQ 411 28 155 30 missing 24 133 26 423 286 29 172

16 BLQ 164 79 273 80 229 58 53 89 78 308 78 224

Sitagliptin Concentration (ng/mL)

AN 1 PK data indicate several potential missed doses;

however, these doses were reported via eDiary and

Smart Packaging

DNA profiling indicates this subject had

someone else collect most of the at-home

samples

Key Take-Aways

Confirmation of patient ID (via DNA profiling or other means) for at-

home samples is useful

“Without (quantitative) data you’re just another person

with an opinion.”

W. Edward Deming

Smart Sampling: Questionnaire Results

20

Smart Trials Pilot #1 (4 samples/day, n=14)

Reduced frequency

of fingerstick

sampling may result

in less pain and help

drive subject

preference toward at

home fingerstick

sampling

MK-X Study (1 sample/day, n=36)

Smart Sampling: Questionnaire Results

21

TAP™ device • Minimally invasive, micro-needle based sampling via push-button

• Painless, no sharp exposure

• This trial used TAP™ for limited in-clinic sampling (performed by clinic staff) to get subject feedback

Fingerstick

TAPTM

If you had a choice, which would you choose to

use in a future clinical trial?

Rationale for choice:

less painful

Rationale for choice:

speed of collection

Fingerstick

via lancet

Less painful methods of sampling may be beneficial in

driving subject preference for at-home sampling

Future of Outpatient Sample Collection

22

Dried blood collection with electronic diary

• Finger stick, spots on DBS card

• Time and date recorded by patient

Neoteryx Mitra

• Fingerstick with accurate volume collection

• Date and time automatically collected

Seventh Sense TAP™ device

• Minimally invasive, micro-needle based

• Painless, no sharp exposure

HemaPen®

• Simplified collection of samples

• Volumetric collection

Tasso HemoLink

• External collection

• Painless, no sharp exposure

Smart Analytics: Preliminary Insights

23

• Multiple devices/apps “universal remote”

• Data capture and integration can be daunting even for a small trial

• External vendors, different data formats, multiple devices, central data management system

• Data management systems/standards not equipped for mHealth and/or two-way communication

• Pilot trials relied on vendor web portals

• Need concerted effort for real-time analytics and visualization of data integrated across data sources

Smart Trials Strategy

24

Smart Trials Clinical Development Plan

Technology Development Trials

Portfolio-facing Opportunities

Focus: •Rapid learn & confirm cycles •Technology “readiness” •Not tethered to a program

Focus: • Enrich datasets (PK, PD, BMx) for program

decisions • Improve trial logistics and efficiency • Shape Regulatory Thinking

Transfer/share knowledge with key adjacencies

Adherence, Effectiveness, ePROs, customer-centric interfaces

Technology Development Trials

EFPIA Survey on Use of Digital Tools in Clinical Development

25

Where can Industry, Academia and Regulators come together?

26

Another “Critical Path Initiative”?

• Steep curve from pilot trials routine application of “smart” approaches

• Partnerships • Complement competencies cross-industry

• Merck doesn’t make apps, Google doesn’t develop drugs

• Pre-competitive technology and platform development

• Shape policy: patient privacy, trial blinding, precision Rx

• Role of Consortia, IQ, CTTI, Transcelerate

The Future!

27

Acknowledgements

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• Kevin Bateman

• Prajakti Kothare

• Jyoti Shah

• Matt Moyer

• Marissa Dockendorf

• Rachel Ruba

• Jane Harrelson

• Gowri Murthy

• Rubi Burlage

• Andra Goldman

• Jeff Sachs

• Stephany Contrella

• Tian Zhao

…and many others on the Smart Trials team

Questions

29